Karthika, D. and Kalaiselvi, K. (2021) Big Data. In: EAI/Springer Innovations in Communication and Computing. Springer, pp. 33-56.
Full text not available from this repository. (Request a copy)Abstract
Healthcare is perhaps one of the most important therapy fields of the new age. Health policy should use a vast variety of analytical knowledge to collect data and measurements of difficulty. It should be beneficial and able to predict patient well-being by evaluating diet, medical history, and social behavior. Hours is a broad health network. Good lifestyle-recommendations are included. Therefore, informal health networks have become critical collective decision-making structures. Maintaining efficient knowledge distribution, performance, security, and secrecy is a crucial goal. The Health Advisory Framework (HRS) is of great value in achieving results such as the analysis of clinical effects, preventive advantages, therapeutic options, and complementary medications focused on patient knowledge databases, and people are utilizing social networks to uncover their health issues. Present research in this chapter on massive amounts of medical data decreases healthcare expenditures by integrating multimodal data from different outlets. Big data analysis utilizing the Advice Platform plays an essential part, offering a smart HRS strategy that provides visibility into how large data analytics can be used as effective health advising engine and how the healthcare system can be transformed from a traditional to a more personalized model into a tele-health setting.
Item Type: | Book Section |
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Subjects: | Computer Science Engineering > Big Data |
Divisions: | Computer Science |
Depositing User: | Mr IR Admin |
Date Deposited: | 10 Oct 2024 05:26 |
Last Modified: | 10 Oct 2024 05:26 |
URI: | https://ir.vistas.ac.in/id/eprint/9632 |